个人信息
参与实验室科研项目
基于数据驱动和联合设计的无线网络化控制系统的使能建模和设计
研究课题
基于近似模型的事件触发模型预测控制、应用于无线网络化控制系统中的模型预测控制方法
学术成果
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Conference Articles
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Approximation-Based Self-Triggered Model Predictive Control for Perturbed Nonlinear Systems
Chang Xu,
Yu Kang,
Yun-Bo Zhao ,
Pengfei Li,
and Tao Wang
In 2021 China Autom. Congr. CAC
2021
[Abs]
[doi]
[pdf]
This paper proposes an approximation-based selftriggered model predictive control strategy for perturbed constrained nonlinear sampled-data systems. In our proposed strategy, the finite horizon optimal control problem (FHOCP) and the triggering condition are designed based on approximate discrete-time models. By implementing the strategy, the computation problem of the FHOCP becomes tractable since it is computed in a discrete-time framework. Meanwhile, the next triggering instant is pre-determined by the triggering condition, reducing the sensing cost and the computing frequency of the FHOCP. Furthermore, feasibility of the FHOCP and stability of the overall system are analyzed. Finally, a simulation example verifies the effectiveness of the strategy.